Jun Dai | Engineering | Best Researcher Award

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Assoc. Prof. Dr. Jun Dai | Engineering | Best Researcher Award

Associate Professor at Beijing institute of technology, China

Dr. Jun Dai is a distinguished researcher whose work has significantly advanced the fields of microfabrication, superconducting devices, and microsystem dynamics. He has built a robust reputation through his innovative research and diverse expertise in smart materials and MEMS technologies. Over the course of his career, Dr. Dai has secured 15 patents, authored 16 refereed journal articles, and delivered more than 30 technical presentations at both national and international conferences. His research is backed by multiple prestigious national projects, including those funded by the National Natural Science Foundation of China and the National Key R&D Program of China, which attest to his leadership and vision in addressing complex engineering challenges. By consistently pushing the boundaries of technology, Dr. Dai has made enduring contributions that benefit academic institutions, industry partners, and the broader scientific community, setting a high standard for excellence and innovation. His exemplary record consistently inspires future researchers worldwide.

Professional Profile 

Education

Dr. Jun Dai’s academic journey laid a robust foundation for his innovative career in engineering and technology. He earned his master’s degree in Mechatronical Engineering from Beijing Institute of Technology in 2010, where he developed a strong background in system dynamics and smart materials. Building on this expertise, he pursued a Ph.D. in Mechanical Engineering at the University of Tokyo, graduating in 2013. His doctoral research, which centered on microfabrication, superconducting devices, and focused-ion-beam chemical vapor deposition, showcased his ability to tackle complex engineering challenges with precision and creativity. Throughout his studies, Dr. Dai was recognized with prestigious awards and scholarships, including support from the China National Scholarship and the China Scholarship Council, affirming his academic excellence. This rigorous educational experience not only honed his technical skills but also instilled a passion for research and innovation that continues to drive his groundbreaking contributions to science and technology. Inspiring his future.

Professional Experience

Dr. Jun Dai’s professional journey is marked by rapid career progression and significant contributions to academia and industry. Beginning his career as a lecturer at Beijing Institute of Technology in 2013, he quickly demonstrated exceptional research and teaching capabilities, leading to his promotion to Associate Professor in 2018. His experience as a visiting researcher at the University of Tokyo in 2015 and 2019 further enriched his international perspective and collaborative skills. Dr. Dai has led high-profile research projects funded by prestigious organizations such as the National Natural Science Foundation of China and the National Key R&D Program of China, underscoring his leadership and innovation. In addition to his research accomplishments, he contributes to the academic community through roles on technical program committees, session chair positions, and as an evaluation expert for major funding bodies. His professional experience reflects a commitment to excellence, interdisciplinary collaboration, and innovation, driving future technological progress.

Research Interest

Dr. Jun Dai’s research interests focus on the integration of microscale engineering and advanced materials science, addressing fundamental challenges in device miniaturization and smart system design. His work spans microfabrication, superconducting devices, and focused-ion-beam chemical vapor deposition, enabling the creation of innovative nanoscale components. Dr. Dai is passionate about exploring the dynamics of microsystems, where the interplay between thermal, electrical, and mechanical fields can be harnessed for enhanced device performance. His research projects include developing thermally driven MEMS optical switches and investigating energy conversion mechanisms in rotary magnetorheological actuators. In addition, he is involved in research on nanoresonator coupling with superconducting circuits and the design of intelligent control systems for high-speed magnetic liquid seals. Through this interdisciplinary approach, Dr. Dai aims to push the boundaries of microelectromechanical systems, contributing both theoretical insights and practical solutions that advance modern engineering applications. His innovative approach continues to inspire new developments and collaborative research efforts.

Award and Honor

Dr. Jun Dai has been recognized with numerous awards and honors that reflect his exceptional contributions to engineering research and innovation. Throughout his career, he has received prestigious accolades, including the China National Scholarship from the China Scholarship Council during his doctoral studies and the JASSO Follow-up Research Fellowship, which recognized his promising research potential. These honors affirm his commitment to excellence and his role as a leading innovator in microfabrication, superconducting devices, and MEMS technology. His recognition extends beyond national boundaries, as international collaborations and accolades have further underscored his impact on the global research community. Dr. Dai’s award portfolio not only celebrates his technical achievements but also highlights his leadership, creative problem-solving, and dedication to advancing microsystem dynamics. These awards serve as a testament to his outstanding research capabilities and inspire both peers and emerging scientists to pursue groundbreaking work in modern engineering disciplines, earning further international prestige.

Research Skill

Dr. Jun Dai demonstrates an impressive array of research skills that combine rigorous theoretical analysis with innovative experimental techniques. His proficiency in microfabrication, particularly using focused-ion-beam chemical vapor deposition, allows him to develop advanced superconducting nanodevices with exceptional precision. Dr. Dai’s expertise spans multiple disciplines, including mechanical engineering, materials science, and electronics, enabling him to tackle complex problems in microsystems and smart material-based devices. He excels in designing controlled experiments, utilizing state-of-the-art instrumentation, and employing sophisticated data analysis methods to validate his hypotheses. His ability to lead large-scale, multidisciplinary projects and secure funding from prestigious bodies such as the National Natural Science Foundation of China is a testament to his research acumen. Furthermore, his strong communication skills are evident in his extensive publication record and international conference presentations, which reflect his commitment to advancing scientific knowledge and fostering collaboration across diverse research fields, demonstrating mastery in innovative research techniques successfully.

Conclusion

Dr. Jun Dai presents a compelling case for the Best Researcher Award. His strong academic credentials, innovative research portfolio, impressive publication and patent record, and significant professional service mark him as an outstanding contributor to his field. With minor enhancements in collaborative efforts, mentorship, and thematic diversification, his already exemplary record positions him as a highly suitable candidate for the award.

Publications Top Noted

Publication 1:
Authors: Wenwu Wang; Zeyu Ma; Qi Shao; Jiangwang Wang; Leixin Wu; Xiyao Huang; Zilu Hu; Nan Jiang; Jun Dai; Liang HE
Year: 2024
Citation: “Multi-MXene assisted large-scale manufacturing of electrochemical biosensors based on enzyme-nanoflower enhanced electrodes for the detection of H₂O₂ secreted from live cancer cells,” Nanoscale, 2024, DOI: 10.1039/d4nr01328j

Publication 2:
Authors: Kai Yang; Zhe Zhu; Xin He; Ruiqi Song; Xiaoqiao Liao; Leixin Wu; Yixue Duan; Chuan Zhao; Muhammad Tahir; Jun Dai et al.
Year: 2024
Citation: “High-performance zinc metal anode enabled by large-scale integration of superior ion transport layer,” Chemical Engineering Journal, July 2024, DOI: 10.1016/j.cej.2024.152114

Publication 3:
Authors: Zeyu Ma; Wenwu Wang; Yibo Xiong; Yihao Long; Qi Shao; Leixin Wu; Jiangwang Wang; Peng Tian; Arif Ullah Khan; Wenhao Yang et al.
Year: 2024
Citation: “Carbon Micro/Nano Machining toward Miniaturized Device: Structural Engineering, Large‐Scale Fabrication, and Performance Optimization,” Small, July 19, 2024, DOI: 10.1002/smll.202400179

Publication 4:
Authors: Haitian Long; Song Tian; Qiulei Cheng; Lingfei Qi; Jun Dai; Yuan Wang; Ping Wang; Sheng Liu; Mingyuan Gao; Yuhua Sun
Year: 2024
Citation: “Highly durable and efficient power management friction energy harvester,” Nano Energy, May 2024, DOI: 10.1016/j.nanoen.2024.109363

Publication 5:
Authors: Tairong Zhu; Tong Wu; Zheng Gao; Jianwen Wu; Qiaofeng Xie; Jun Dai
Year: 2024
Citation: “Anti-sedimentation mechanism of rotary magnetorheological brake integrating multi-helix microstructure,” International Journal of Mechanical Sciences, March 2024, DOI: 10.1016/j.ijmecsci.2024.108980

Publication 6:
Authors: Jun Dai; Changlei Feng; Jin Xie; Mingyuan Gao; Tao Zhen
Year: 2023
Citation: “Design and Control of an Analog Optical Switch Based on the Coupling of an Electrothermal Actuator and a Mass–Spring System,” IEEE/ASME Transactions on Mechatronics, 2023, DOI: 10.1109/tmech.2023.3238109

Publication 7:
Authors: Shuai Yang; Yumei Li; Ling Deng; Song Tian; Ye Yao; Fan Yang; Changlei Feng; Jun Dai; Ping Wang; Mingyuan Gao
Year: 2023
Citation: “Flexible thermoelectric generator and energy management electronics powered by body heat,” Microsystems & Nanoengineering, August 24, 2023, DOI: 10.1038/s41378-023-00583-3

Jinsheng Liang | Engineering | Best Researcher Award

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Dr. Jinsheng Liang | Engineering | Best Researcher Award

PhD Candidate at Shenyang Institute of Automation, Chinese Academy of Science, China

Dr. Jinsheng Liang is a distinguished researcher specializing in ultra-precision machining and water jet-guided laser technology. He earned his Bachelor of Engineering from Wuhan University of Technology and is currently pursuing a Doctorate in Engineering at the Shenyang Institute of Automation, Chinese Academy of Sciences. His research focuses on fluid flow characteristics, laser transmission mechanisms, and high-efficiency milling techniques, contributing to advancements in precision manufacturing. Dr. Liang has played a key role in national research projects, particularly in enhancing the stability and efficiency of light-guiding liquid beams in laser processing. He has published five high-impact papers in The International Journal of Advanced Manufacturing Technology and Optics & Laser Technology, demonstrating expertise in fluid simulation and mechanical manufacturing. With strong technical skills and a commitment to innovation, Dr. Liang continues to push the boundaries of laser machining technology, aiming to bridge the gap between academic research and industrial applications.

Professional Profile 

Education

Dr. Jinsheng Liang has a strong academic background in mechanical engineering and ultra-precision machining. He is currently pursuing a Doctor of Engineering at the Shenyang Institute of Automation, Chinese Academy of Sciences, specializing in mechanical manufacturing and automation. His doctoral research focuses on water jet-guided laser technology, fluid flow simulation, and high-precision machining. Prior to this, he earned his Bachelor of Engineering in mechanical design, manufacturing, and automation from Wuhan University of Technology in 2019. Throughout his academic journey, Dr. Liang has gained extensive expertise in laser machining techniques, fluid dynamics, and numerical simulations, contributing to cutting-edge research in precision manufacturing. His educational background, combined with hands-on research experience, has positioned him as a promising expert in his field, bridging theoretical knowledge with practical applications to advance high-efficiency laser processing technologies.

Professional Experience

Dr. Jinsheng Liang has extensive research experience in ultra-precision machining and water jet-guided laser technology. Since 2019, he has been pursuing his Doctor of Engineering at the Shenyang Institute of Automation, Chinese Academy of Sciences, where he has been actively involved in national research projects. His key contributions include research on laser electrolysis composite high-efficiency milling technology and the stability of internal light-guiding liquid beams and laser transmission mechanisms. He has utilized Fluent software for fluid simulations, combining theoretical modeling with experimental validation to enhance laser machining precision. Dr. Liang has published five high-impact papers in renowned journals, solidifying his expertise in laser technology, fluid simulation, and mechanical manufacturing. His work significantly contributes to advancements in high-precision manufacturing, and his ability to integrate research findings with industrial applications underscores his potential as a leading researcher in laser machining and automation.

Research Interest

Dr. Jinsheng Liang’s research interests lie in the fields of laser technology, fluid simulation, and mechanical manufacturing, with a particular focus on ultra-precision machining and water jet-guided laser technology. His work explores fluid flow characteristics, laser transmission mechanisms, and high-efficiency milling techniques, aiming to improve the precision and stability of laser processing. He specializes in the numerical simulation of liquid-guided laser beams, using Fluent software to model fluid behavior and enhance machining accuracy. His research also extends to the development of advanced laser processing methods for complex materials, with potential applications in aerospace, electronics, and high-tech manufacturing. Through his studies, Dr. Liang seeks to bridge the gap between theoretical modeling and experimental validation, contributing to the advancement of next-generation laser machining technologies. His expertise in precision engineering and automation positions him as a key contributor to the future of high-precision manufacturing.

Award and Honor

Currently, there are no explicitly listed awards and honors for Dr. Jinsheng Liang. However, his significant contributions to ultra-precision machining and water jet-guided laser technology highlight his growing impact in the field of mechanical manufacturing and automation. As a doctoral researcher at the Shenyang Institute of Automation, Chinese Academy of Sciences, he has been actively involved in national research projects, demonstrating excellence in fluid simulation, laser transmission mechanisms, and high-efficiency milling techniques. His five high-impact publications in prestigious journals, such as The International Journal of Advanced Manufacturing Technology and Optics & Laser Technology, reflect the recognition of his work within the scientific community. Given his expertise and research accomplishments, Dr. Liang is a strong candidate for future academic awards, industry recognitions, and research grants. His contributions to precision laser machining and automation continue to position him as an emerging leader in the field.

Research Skill

Dr. Jinsheng Liang possesses advanced research skills in laser technology, fluid simulation, and mechanical manufacturing, with a strong focus on ultra-precision machining and water jet-guided laser technology. He is proficient in numerical simulation and computational fluid dynamics (CFD), utilizing Fluent software to analyze fluid flow characteristics and laser transmission mechanisms. His expertise extends to experimental validation, where he integrates simulation results with real-world laser machining processes to enhance precision and efficiency. Dr. Liang has a deep understanding of laser-material interactions, milling techniques, and high-efficiency processing methods, allowing him to contribute to cutting-edge manufacturing advancements. His ability to design and execute complex experiments, analyze large datasets, and optimize machining parameters makes him a valuable researcher in the field. With five high-impact journal publications, he demonstrates strong skills in technical writing, data interpretation, and problem-solving, essential for advancing high-precision laser processing technologies.

Conclusion

Jinsheng Liang is a strong candidate for the Best Researcher Award due to his specialized expertise, impactful research, and high-quality publications. His contributions to ultra-precision machining and laser technology are commendable, and his ability to conduct numerical simulations and experimental studies is impressive. Strengthening industry impact and international collaboration would further elevate his profile.

Publications Top Noted

Authors: Jinsheng Liang, Hongchao Qiao, Jibin Zhao, Yuting Zhang, Qing Zhang
Year: 2025
Journal: Optics and Laser Technology
Title: Simulation and experimental study on double staggered-axis air-assisted water jet-guided laser film cooling hole machining

Yi Sun | Engineering | Best Researcher Award

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Dr. Yi Sun | Engineering | Best Researcher Award

Southwest Jiaotong University, China

Dr. Yi Sun is a distinguished researcher specializing in equipment status monitoring, health indicator construction, and deep learning applications. Currently pursuing a Ph.D. in Mechanical and Electronic Engineering at Southwest Jiaotong University, he has an impressive academic track record with 12 published papers, including 7 SCI papers, 4 of which are in top-tier JCR Q1 journals. His research contributions include developing predictive maintenance algorithms, process parameter optimization, and aerodynamic identification models for hypersonic wind tunnels. He has also led industry projects in predictive maintenance systems and multi-source aerodynamic data fusion. Recognized with multiple National Scholarships and industry accolades such as Huawei’s “Rising Star” award, Dr. Sun demonstrates exceptional expertise in both academic research and practical applications. His work bridges the gap between theoretical advancements and industrial innovation, positioning him as a leading figure in mechanical engineering and deep learning-based monitoring systems.

Professional Profile 

Education

Dr. Yi Sun has a strong educational background in mechanical engineering and electronic systems. He earned his Bachelor’s degree in Mechanical Engineering and Automation from Zhengzhou University (2012-2016), where he built a solid foundation in engineering principles. He then pursued a Master’s degree in Mechanical Engineering at Southwest Jiaotong University (2017-2020), where he gained expertise in advanced manufacturing processes, equipment monitoring, and fault diagnosis. Currently, he is undertaking a Ph.D. in Mechanical and Electronic Engineering at Southwest Jiaotong University (2021-2025), focusing on deep learning applications, health indicator construction, and predictive maintenance for industrial systems. Throughout his academic journey, he has been recognized with prestigious honors, including National Scholarships and Outstanding Graduate Student awards. His education has provided him with a unique blend of theoretical knowledge and practical experience, enabling him to contribute significantly to both academia and industry in the fields of mechanical engineering and intelligent monitoring systems.

Professional Experience

Dr. Yi Sun has a diverse professional background spanning both academia and industry. He worked as an R&D Engineer at Huawei Technologies Co., Ltd. (2020-2021), where he contributed to cutting-edge research and development in predictive maintenance and equipment monitoring. His industry experience provided him with hands-on expertise in software and hardware integration, sensor selection, and algorithm development for real-world applications. As a Ph.D. researcher at Southwest Jiaotong University (2021-present), he has led multiple high-impact projects, including the development of predictive maintenance systems for CNC machine tools and multi-source aerodynamic data fusion models for the China Aerodynamics Research and Development Center. His research has resulted in 12 published papers, several in top-tier journals, and numerous awards for academic excellence. Dr. Sun’s professional journey demonstrates his ability to bridge the gap between theoretical research and industrial innovation, making significant contributions to mechanical engineering and deep learning-based monitoring technologies.

Research Interest

Dr. Yi Sun’s research interests lie at the intersection of mechanical engineering, deep learning, and intelligent monitoring systems. His work focuses on equipment status monitoring, health indicator construction, fault diagnosis, and predictive maintenance for industrial applications. He specializes in process parameter optimization, particularly in milling cutter status assessment, utilizing advanced signal analysis, noise reduction, and online monitoring techniques. His expertise extends to deep learning-based fault detection, including the development of aerodynamic force identification models and transfer learning techniques for aerodynamic data analysis in hypersonic wind tunnels. Dr. Sun is also engaged in multi-source data fusion, enhancing accuracy and consistency in industrial systems. His research aims to optimize mechanical performance, reduce downtime, and improve system reliability through AI-driven solutions. By integrating machine learning with mechanical systems, he contributes to advancing intelligent manufacturing, predictive maintenance, and next-generation industrial automation technologies.

Award and Honor

Dr. Yi Sun has received numerous prestigious awards and honors in recognition of his outstanding academic and research achievements. During his master’s and Ph.D. studies, he was awarded the National Scholarship, one of the highest academic honors in China, for his excellence in research and academics. He was also recognized as an Outstanding Graduate Student at both the university and provincial levels. His exceptional contributions to mechanical engineering and intelligent monitoring systems earned him the Mingcheng Award and the Comprehensive Quality A-Level Certificate during his postgraduate studies. In the corporate sector, he was honored as an Excellent Student in Huawei’s New Employee Training Camp and received the Huawei “Rising Star” Award for his innovative contributions. These accolades reflect his dedication, innovation, and leadership in academia and industry. Dr. Sun’s achievements highlight his remarkable research capabilities and his potential to drive advancements in intelligent manufacturing and predictive maintenance systems.

Research Skill

Dr. Yi Sun possesses exceptional research skills in mechanical engineering, deep learning, and intelligent monitoring systems. His expertise includes equipment status monitoring, fault diagnosis, health indicator construction, and predictive maintenance. He is proficient in signal processing, noise reduction, and multi-source data fusion, enabling accurate real-time monitoring and fault prediction for industrial systems. His strong foundation in deep learning and machine learning algorithms allows him to develop advanced models for aerodynamic force identification and process parameter optimization. Dr. Sun is skilled in software and hardware development, including sensor selection, data acquisition, edge computing, and algorithm integration for predictive maintenance systems. He also excels in scientific writing, publishing high-impact research in top-tier journals and presenting at international conferences. His ability to combine theoretical research with practical industrial applications demonstrates his versatility and innovation, making significant contributions to the advancement of intelligent manufacturing and mechanical system optimization.

Conclusion

Sun Yi is highly suitable for the Best Researcher Award due to his exceptional publication record, innovative contributions to equipment status monitoring and deep learning, industry experience, and leadership in research projects. While he could enhance his application with patents, tech commercialization, and broader collaborations, his current achievements make him a strong candidate for the award. 🚀

Publications Top Noted

  • L. Wei, Y. Sun, J. Zeng, S. Qu (2022). “Experimental and numerical investigation of fatigue failure for metro bogie cowcatchers due to modal vibration and stress induced by rail corrugation.” Engineering Failure Analysis, 142, 106810. Citations: 31

  • Y. Sun, L. Wei, C. Liu, H. Dai, S. Qu, W. Zhao (2022). “Dynamic stress analysis of a metro bogie due to wheel out-of-roundness based on multibody dynamics algorithm.” Engineering Failure Analysis, 134, 106051. Citations: 22

  • J. Mu, J. Zeng, C. Huang, Y. Sun, H. Sang (2022). “Experimental and numerical investigation into development mechanism of wheel polygonalization.” Engineering Failure Analysis, 136, 106152. Citations: 21

  • Y. Li, H. Dai, Y. Qi, S. Qu, Y. Sun (2023). “Experimental study of bogie instability monitoring and suppression measures for high-speed EMUs.” Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit. Citations: 6

  • Y. Sun, L. Wei, H. Dai, C. Liu, S. Qu, Y. Qi (2023). “Influence of rail weld irregularity on dynamic stress of bogie frame based on vehicle-track rigid-flexible coupled model.” Journal of Vibration and Control, 29 (17-18), 4172-4185. Citations: 5

  • Y. Sun, L. Wei, S. Qu, H. Dai (2024). “Fatigue stress estimation of metro bogie frame through frequency response functions by using limited sensors.” Structural Health Monitoring, 23 (1), 421-442. Citations: 2

  • Y. Sun, L. Wei, H. Dai (2024). “Indirect Dynamic Stress Measurement of Metro Bogie Using LSTM Network in Frequency Domain.” IEEE Sensors Journal.

Dr Mahmood Al-Shareeda | Engineering | Best Researcher Award |

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🌟Dr. Mahmood Al-Shareeda, Engineering, Best Researcher Award🏆

Iraq University College, Iraq

Professional Profiles : 

Scopus Profile

Google Scholar Profile

Orcid Profile

👩‍🎓 Bio Summary:

Dr. Mahmood Al-Shareeda is a highly accomplished researcher specializing in cybersecurity and advanced networking. He holds a Bachelor’s Degree in Communication Engineering, a Master’s Degree in Computer & Communication Engineering, and a Ph.D. in Internet Infrastructure Security. With expertise in VANET and IoT security, wireless communication, and cryptography, Dr. Al-Shareeda’s work focuses on developing secure communication protocols for emerging technologies. He has held research positions at institutions such as Universiti Sains Malaysia and the University of Ha’il, contributing to projects ranging from quantum-resistant schemes to blockchain-based secure data sharing among vehicles.

🎓 Education:

Dr. Mahmood Al-Shareeda holds a Bachelor’s Degree in Communication Engineering from Iraq University College, a Master’s Degree in Computer & Communication Engineering from the Islamic University of Lebanon, and a Ph.D. in Internet Infrastructure Security from Universiti Sains Malaysia. Additionally, he completed speaking English courses at the English Language Institute of Symbiosis in India and pursued a Doctorate in Business Administration from the British Institute of Economics and Political Science in the UK.

👩‍💼 Professional Experience:

Dr. Al-Shareeda’s professional journey spans various research and academic roles. He served as a Postdoctoral Fellow at Universiti Sains Malaysia, focusing on authentication and privacy-preserving schemes for 5G-enabled vehicular fog computing. He also held research positions at the University of Ha’il in Saudi Arabia, contributing to projects such as quantum-resistant schemes and blockchain-based secure data sharing among vehicles.

🔬 Research Focus:

With expertise in VANET and IoT security, wireless communication, and classical and quantum cryptography, Dr. Al-Shareeda’s research interests lie at the intersection of cutting-edge technologies and cybersecurity. His work delves into developing efficient and secure communication protocols for emerging technologies.

🚀 Professional Journey:

Beginning his career with academic pursuits in communication engineering, Dr. Al-Shareeda’s trajectory evolved into the realm of cybersecurity and advanced networking. He transitioned from academia to research roles, actively contributing to projects aimed at enhancing the security and efficiency of communication networks, particularly in the context of emerging technologies like 5G and vehicular networks.

🏅 Honors & Awards:

Dr. Al-Shareeda’s contributions have been recognized with numerous honors and awards, reflecting his dedication and excellence in research. His achievements include notable distinctions such as research grants, scholarships, and accolades for his impactful publications and contributions to the field.

📚 Top Noted Publications & Contributions:

Survey of Authentication and Privacy Schemes in Vehicular Ad Hoc Networks

Authors: MA Al-shareeda, M Anbar, IH Hasbullah, S Manickam

Published in IEEE Sensors Journal in 2021

Citations: 126

VPPCS: VANET-based Privacy-Preserving Communication Scheme

Authors: MA Al-Shareeda, M Anbar, S Manickam, AA Yassin

Published in IEEE Access in 2020

Citations: 83

Efficient Conditional Privacy Preservation with Mutual Authentication in Vehicular Ad Hoc Networks

Authors: MA Al-Shareeda, M Anbar, IH Hasbullah, S Manickam, SM Hanshi

Published in IEEE Access in 2020

Citations: 51

SE-CPPA: A Secure and Efficient Conditional Privacy-Preserving Authentication Scheme in Vehicular Ad-Hoc Networks

Authors: MA Al-Shareeda, M Anbar, S Manickam, IH Hasbullah

Published in Sensors (Special Issue Recent Trends in Wireless Sensor and Actuator) in 2021

Citations: 48

Review of Prevention Schemes for Replay Attack in Vehicular Ad hoc Networks (VANETs)

Authors: MA Al-shareeda, M Anbar, IH Hasbullah, S Manickam, N Abdullah

Presented at the 2020 IEEE 3rd International Conference on Information Communication and Technology (ICICT)

Citations: 46

📊 Author Metrics:

Dr. Al-Shareeda’s impact in the academic community is reflected in his author metrics, with an impressive publication record, substantial citation counts, and a notable H-index across various platforms. His contributions to the field demonstrate both depth and breadth, underscoring his influence in advancing research in cybersecurity and communication engineering.

⏳ Research Timeline:

Dr. Al-Shareeda’s research journey has been characterized by a timeline marked with significant milestones and achievements. From his foundational education in communication engineering to his current role as a respected researcher specializing in cybersecurity and advanced networking, each phase of his career has contributed to his expertise and impact in the field.